Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/39996
Title: Application of Satellite-Based Precipitation Estimates to Rainfall-Runoff Modelling in a Data-Scarce Semi-Arid Catchment
Authors: Najmaddin, Peshawa M.
Whelan, Mick J.
Balzter, Heiko
First Published: 11-Apr-2017
Publisher: MDPI
Citation: Climate, 2017, 5 (2), pp. 32-32
Abstract: Rainfall-runoff modelling is a useful tool for water resources management. This study presents a simple daily rainfall-runoff model, based on the water balance equation, which we apply to the 11,630 km2 Lesser Zab catchment in northeast Iraq. The model was forced by either observed daily rain gauge data from four stations in the catchment or satellite-derived rainfall estimates from two TRMM Multi-satellite Precipitation Analysis (TMPA) data products (TMPA-3B42 and 3B42RT) based on the Tropical Rainfall Measuring Mission (TRMM) from 2003 to 2014. As well as using raw TMPA data, we used a bias-correction method to adjust TMPA values based on rain gauge data. The uncorrected TMPA data products underestimated observed mean catchment rainfall by −10.1% and −10.7%. Corrected data also slightly underestimated gauged rainfall by −0.7% and −1.6%, respectively. Nash-Sutcliffe Efficiency (NSE) and Pearson’s Correlation Coefficient (r) for the model fit with the observed hydrograph were 0.75 and 0.87, respectively, for a calibration period (2010–2011) using gauged rainfall data. Model validation performance (2012–2014) was best (highest NSE and r; lowest RMSE and bias) using the corrected 3B42 data product and poorest when driven by uncorrected 3B42RT data. Uncertainty and equifinality were also explored. Our results suggest that TRMM data can be used to drive rainfall-runoff modelling in semi-arid catchments, particularly when corrected using rain gauge data.
DOI Link: 10.3390/cli5020032
ISSN: 2225-1154
eISSN: 2225-1154
Links: http://www.mdpi.com/2225-1154/5/2/32
http://hdl.handle.net/2381/39996
Version: Publisher Version
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © the authors, 2017. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Description: Supplementary Materials: The following are available online at www.mdpi.com/2225-1154/5/2/32/s1.
Appears in Collections:Published Articles, Dept. of Geography

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